arXiv subjects

Zhiyuan Sun

Publications and source records attributed to Zhiyuan Sun.

At least 37 records · Page 2Linked to original sources

arXiv2025

Interaction effects on electronic Floquet spectra: Excitonic effects

Floquet engineering of electronic states by light is a central topic in modern experiments. However, the impact of many-body interactions on the single-electron properties remains unclear in this non-equilibrium situation. We propose that interaction effects could be reasonably understood by performing perturbative expansion in both the pump field and the electron-electron interaction when computing physical quantities. As an example, we apply this approach to semiconductors and show analytically that excitonic effects, i.e., effects of electron-hole interaction, lead to dramatic corrections to the single-electron Floquet spectra even when the excitons are only virtually excited by the pump light. We compute these effects in phosphorene and monolayer MoS$_2$ for time- and angle-resolved photoemission spectroscopy and ultrafast optical experiments.

cond-mat.other↗

arXiv2025

High-order staggered Lagrangian hydrodynamics (II) : the artificial viscosity and hourglass control algorithm

In this article, we investigate the artificial viscosity and hourglass control algorithms for high-order staggered Lagrangian hydrodynamics(SGH), as proposed in~\cite[Sun et al., 2025]{Sun2025High}. Inspired by the subzonal pressure method in classical staggered Lagrangian hydrodynamics, we extend the stiffness-based hourglass control algorithm to the high-order setting, enriching the pressure field from the $Q^{m-1}$ to the $Q^{m}$ polynomial space. A unified framework for this hourglass control approach is established, from which the classical subzonal pressure method naturally emerges as the special case of the $Q^1-P^0$ space. The artificial viscosity follows the formulation in~\cite[Dobrev et al., 2012]{Dobrev2012High}. We show that the viscosity admits a concise form, with intermediate variables explicitly computable, leading to improved computational efficiency and easier implementation. Moreover, the tensor viscosity in classical staggered Lagrangian hydrodynamics can be derived in a similarly compact and explicit form. Numerical experiments on two-dimensional problems are presented to demonstrate the accuracy and efficiency of the proposed algorithms.

math.NA↗

arXiv2025

Observation of Local Pairs through Nonequilibrium Terahertz Spectroscopy in YBa2Cu3O7-δ Below Tc

Pairing states are essential to understanding the underlying mechanisms of high-temperature superconductivity. Here the non-superconducting state in an optimally doped YBa_2 Cu_3 O_(7-δ) film was driven out of equilibrium by an optical pump with low fluence at a temperature well below the critical temperature (T_c), and its recovery dynamics were exclusively measured using transient terahertz spectroscopy. The pump-fluence dependent experiments unveiled evidence of local pairs without superconductivity coexisting with the superconducting Cooper pairs. An energy gap opening induced by the local pairing with short-range coherence was invoked to rationalize the temperature-dependent recovery time of local pairs with a characteristic divergence at a temperature substantially below T_c. These local pairs displayed remarkable likeness to the short-range pair-density-wave state. Our finding sheds light on understanding the dynamic interplay between the coexisting superconducting and non-superconducting pairs in cuprate superconductors.

cond-mat.supr-con↗

arXiv2025

H2-MARL: Multi-Agent Reinforcement Learning for Pareto Optimality in Hospital Capacity Strain and Human Mobility during Epidemic

The necessity of achieving an effective balance between minimizing the losses associated with restricting human mobility and ensuring hospital capacity has gained significant attention in the aftermath of COVID-19. Reinforcement learning (RL)-based strategies for human mobility management have recently advanced in addressing the dynamic evolution of cities and epidemics; however, they still face challenges in achieving coordinated control at the township level and adapting to cities of varying scales. To address the above issues, we propose a multi-agent RL approach that achieves Pareto optimality in managing hospital capacity and human mobility (H2-MARL), applicable across cities of different scales. We first develop a township-level infection model with online-updatable parameters to simulate disease transmission and construct a city-wide dynamic spatiotemporal epidemic simulator. On this basis, H2-MARL is designed to treat each division as an agent, with a trade-off dual-objective reward function formulated and an experience replay buffer enriched with expert knowledge built. To evaluate the effectiveness of the model, we construct a township-level human mobility dataset containing over one billion records from four representative cities of varying scales. Extensive experiments demonstrate that H2-MARL has the optimal dual-objective trade-off capability, which can minimize hospital capacity strain while minimizing human mobility restriction loss. Meanwhile, the applicability of the proposed model to epidemic control in cities of varying scales is verified, which showcases its feasibility and versatility in practical applications.

cs.MA↗

arXiv2025

Fate of transient order parameter domain walls in ultrafast experiments

In ultrafast experiments, an optical pump pulse often generates transient domain walls of the order parameter in materials with spontaneous symmetry breaking, due to either a finite penetration depth of light on a three-dimensional (3D) material, or a finite spot size on a two-dimensional (2D) material. We show that the domain wall decays due to unstable order parameter fluctuations. We study a generic system with $U(1)$-symmetric order, and those with an additional weak $Z_2$ ($U(1)$-symmetry-breaking) term, representing the charge-density-wave (CDW) orders in recent experiments. During the first stage of the decay dynamics, exponentially growing thermal fluctuations convert the domain wall into an interface with randomly distributed topological defects. In the second stage, the topological defects undergo a coarsening dynamics within the interface. For a 2D interface in a 3D system, the coarsening dynamics leads to a diffusive growth of the correlation length. For a one-dimensional (1D) interface in a 2D system with the weak $Z_2$ term, the correlation-length growth shows a crossover from diffusive to sub-diffusive behavior.

cond-mat.str-el↗

arXiv2024

Manipulating the symmetry of photon-dressed electronic states

Strong light-matter interaction provides opportunities for tailoring the physical properties of quantum materials on the ultrafast timescale by forming photon-dressed electronic states, i.e., Floquet-Bloch states. While the light field can in principle imprint its symmetry properties onto the photon-dressed electronic states, so far, how to experimentally detect and further engineer the symmetry of photon-dressed electronic states remains elusive. Here by utilizing time- and angle-resolved photoemission spectroscopy (TrARPES) with polarization-dependent study, we directly visualize the parity symmetry of Floquet-Bloch states in black phosphorus. The photon-dressed sideband exhibits opposite photoemission intensity to the valence band at the $Γ$ point,suggesting a switch of the parity induced by the light field. Moreover, a "hot spot" with strong intensity confined near $Γ$ is observed, indicating a momentum-dependent modulation beyond the parity switch. Combining with theoretical calculations, we reveal the light-induced engineering of the wave function of the Floquet-Bloch states as a result of the hybridization between the conduction and valence bands with opposite parities, and show that the "hot spot" is intrinsically dictated by the symmetry properties of black phosphorus. Our work suggests TrARPES as a direct probe for the parity of the photon-dressed electronic states with energy- and momentum-resolved information, providing an example for engineering the wave function and symmetry of such photon-dressed electronic states via Floquet engineering.

cond-mat.mes-hall↗

arXiv2024

Semi-Dirac Fermions in a Topological Metal

Topological semimetals with massless Dirac and Weyl fermions represent the forefront of quantum materials research. In two dimensions (2D), a peculiar class of fermions that are massless in one direction and massive in the perpendicular direction was predicted sixteen years ago. These highly exotic quasiparticles - the semi-Dirac fermions - ignited intense theoretical and experimental interest but remain undetected. Using magneto-optical spectroscopy, we demonstrate the defining feature of semi-Dirac fermions - $B^{2/3}$ scaling of Landau levels - in a prototypical nodal-line metal ZrSiS. In topological metals, including ZrSiS, nodal-lines extend the band degeneracies from isolated points to lines, loops or even chains in the momentum space. With $\textit{ab initio}$ calculations and theoretical modeling, we pinpoint the observed semi-Dirac spectrum to the crossing points of nodal-lines in ZrSiS. Crossing nodal-lines exhibit a continuum absorption spectrum but with singularities that scale as $B^{2/3}$ at the crossing. Our work sheds light on the hidden quasiparticles emerging from the intricate topology of crossing nodal-lines and highlights the potential to explore quantum geometry with linear optical responses.

cond-mat.mtrl-sci↗

arXiv2024

Optical signatures of dynamical excitonic condensates

We theoretically study dynamical excitonic condensates occurring in bilayers with an imposed chemical potential difference and in photodoped semiconductors. We show that optical spectroscopy can experimentally identify phase-trapped and phase-delocalized dynamical regimes of condensation. In the weak-bias regime, the trapped dynamics of the order parameter's phase lead to an in-gap absorption line at a frequency almost independent of the bias voltage, while for larger biases, the frequency of the spectral feature increases approximately linearly with bias. In both cases there is a pronounced second harmonic response. Close to the transition between the trapped and freely oscillating states, we find a strong response upon application of a weak electric probe field and compare the results to those found in a minimal model description for the dynamics of the order parameter's phase and analyze the limitations of the latter.

cond-mat.str-el↗

arXiv2024

Enhancing Agent Learning through World Dynamics Modeling

Large language models (LLMs) have been increasingly applied to tasks in language understanding and interactive decision-making, with their impressive performance largely attributed to the extensive domain knowledge embedded within them. However, the depth and breadth of this knowledge can vary across domains. Many existing approaches assume that LLMs possess a comprehensive understanding of their environment, often overlooking potential gaps in their grasp of actual world dynamics. To address this, we introduce Discover, Verify, and Evolve (DiVE), a framework that discovers world dynamics from a small number of demonstrations, verifies the accuracy of these dynamics, and evolves new, advanced dynamics tailored to the current situation. Through extensive evaluations, we assess the impact of each component on performance and compare the dynamics generated by DiVE to human-annotated dynamics. Our results show that LLMs guided by DiVE make more informed decisions, achieving rewards comparable to human players in the Crafter environment and surpassing methods that require prior task-specific training in the MiniHack environment.

cs.AI↗

arXiv2024

Floquet engineering of many-body states by the ponderomotive potential

The ponderomotive force is an effective static force that a particle feels in an oscillating field, whose static potential may be called the ponderomotive potential. We generalize this notion to periodically driven quantum many-body systems, and propose it as a convenient tool to engineer their non-equilibrium steady states beyond the single particle level. Applied to materials driven by light, the ponderomotive potential is intimately related to the equilibrium optical conductivity, which is enhanced close to resonances. We show that the ponderomotive potential from the incident light may be used to induce exciton condensates in semiconductors, to generate attractive interactions leading to superconductivity in certain electron-phonon systems, and to create additional free energy minima in systems with charge/spin/excitonic orders. These effects are presented with experimentally relevant parameters.

cond-mat.str-el↗

arXiv2024

Deep learning analysis of polaritonic waves images

Deep learning (DL) is an emerging analysis tool across sciences and engineering. Encouraged by the successes of DL in revealing quantitative trends in massive imaging data, we applied this approach to nano-scale deeply sub-diffractional images of propagating polaritonic waves in complex materials. We developed a practical protocol for the rapid regression of images that quantifies the wavelength and the quality factor of polaritonic waves utilizing the convolutional neural network (CNN). Using simulated near-field images as training data, the CNN can be made to simultaneously extract polaritonic characteristics and materials parameters in a timescale that is at least three orders of magnitude faster than common fitting/processing procedures. The CNN-based analysis was validated by examining the experimental near-field images of charge-transfer plasmon polaritons at Graphene/α-RuCl3 interfaces. Our work provides a general framework for extracting quantitative information from images generated with a variety of scanning probe methods.

cond-mat.mtrl-sci↗

arXiv2024

Plasmonic polarization sensing of electrostatic superlattice potentials

Plasmon polaritons are formed by coupling light with delocalized electrons. The half-light and half-matter nature of plasmon polaritons endows them with unparalleled tunability via a range of parameters, such as dielectric environments and carrier density. Therefore, plasmon polaritons are expected to be tuned when in proximity to polar materials since the carrier density is tuned by an electrostatic potential; conversely, the plasmon polariton response might enable the sensing of polarization. Here, we use infrared nano-imaging and nano-photocurrent measurements to investigate heterostructures composed of graphene and twisted hexagonal boron nitride (t-BN), with alternating polarization in a triangular network of moiré stacking domains. We observe that the carrier density and the corresponding plasmonic response of graphene are modulated by polar domains in t-BN. In addition, we demonstrate that the nanometer-wide domain walls of graphene moirés superlattices, created by the polar domains of t-BN, provide momenta to assist the plasmonic excitations. Furthermore, our studies establish that the plasmon of graphene could function as a delicate sensor for polarization textures. The evolution of polarization textures in t-BN under uniform electric fields is tomographically examined via plasmonic imaging. Strikingly, no noticeable polarization switching is observed under applied electric fields up to 0.23 V/nm, at variance with transport reports. Our nano-images unambiguously reveal that t-BN with triangular domains acts like a ferrielectric, rather than ferroelectric claimed by many previous studies.

cond-mat.mes-hall↗

arXiv2024

On the Adequacy of the Dynamical Mean Field Theory for Low Density and Dirac Materials

The qualitative reliability of the dynamical mean field theory (DMFT) is investigated for systems in which either the actual carrier density or the effective carrier density is low, by comparing the exact perturbative and dynamical mean field expressions of electron scattering rates and optical conductivities. We study two interacting systems: tight binding models in which the chemical potential is near a band edge and Dirac systems in which the chemical potential is near the Dirac point. In both systems it is found that DMFT underestimates the low frequency, near-Fermi surface single particle scattering rate by a factor proportional to the particle density. The quasiparticle effective mass is qualitatively incorrect for the low density tight binding model but not necessarily for Dirac systems. The dissipative part of the optical conductivity is more subtle: in the exact calculation vertex corrections, typically neglected in DMFT calculations, suppress the low frequency optical absorption, compensating for some of the DMFT underestimate of the scattering rate. The role of vertex corrections in calculating the conductivity for Dirac systems is clarified and a systematic discussion is given of the approach to the Galilean/Lorentz invariant low density limit. Relevance to recent calculations related to Weyl metals is discussed.

cond-mat.str-el↗

arXiv2024

OPEx: A Component-Wise Analysis of LLM-Centric Agents in Embodied Instruction Following

Embodied Instruction Following (EIF) is a crucial task in embodied learning, requiring agents to interact with their environment through egocentric observations to fulfill natural language instructions. Recent advancements have seen a surge in employing large language models (LLMs) within a framework-centric approach to enhance performance in embodied learning tasks, including EIF. Despite these efforts, there exists a lack of a unified understanding regarding the impact of various components-ranging from visual perception to action execution-on task performance. To address this gap, we introduce OPEx, a comprehensive framework that delineates the core components essential for solving embodied learning tasks: Observer, Planner, and Executor. Through extensive evaluations, we provide a deep analysis of how each component influences EIF task performance. Furthermore, we innovate within this space by deploying a multi-agent dialogue strategy on a TextWorld counterpart, further enhancing task performance. Our findings reveal that LLM-centric design markedly improves EIF outcomes, identify visual perception and low-level action execution as critical bottlenecks, and demonstrate that augmenting LLMs with a multi-agent framework further elevates performance.

cs.AI↗

arXiv2024

Deciphering Digital Detectives: Understanding LLM Behaviors and Capabilities in Multi-Agent Mystery Games

In this study, we explore the application of Large Language Models (LLMs) in \textit{Jubensha}, a Chinese detective role-playing game and a novel area in Artificial Intelligence (AI) driven gaming. We introduce the first dataset specifically for Jubensha, including character scripts and game rules, to foster AI agent development in this complex narrative environment. Our work also presents a unique multi-agent interaction framework using LLMs, allowing AI agents to autonomously engage in this game. To evaluate the gaming performance of these AI agents, we developed novel methods measuring their mastery of case information and reasoning skills. Furthermore, we incorporated the latest advancements in in-context learning to improve the agents' performance in information gathering, murderer identification, and logical reasoning. The experimental results validate the effectiveness of our proposed methods. This work aims to offer a novel perspective on understanding LLM capabilities and establish a new benchmark for evaluating large language model-based agents.

cs.AI↗

arXiv2023

Dynamical exciton condensates in biased electron-hole bilayers

Bilayer materials may support interlayer excitons comprised of electrons in one layer and holes in the other. In experiments, a non-zero exciton density is typically sustained by a bias chemical potential, implemented either by optical pumping or by electrical contacts connected to the two layers. We show that if charge can tunnel between the layers, the chemical potential bias means that an exciton condensate is in the dynamical regime of ac Josephson effect. It has physical consequences such as tunneling currents and the ability to tune a condensate from bright (emitting coherent photons) to dark by experimental controlling knobs. If the system is placed in an optical cavity, coupling with cavity photons favors different dynamical states depending on the bias, realizing superradiant phases.

cond-mat.mes-hall↗

arXiv2023

Exciton-spin interactions in antiferromagnetic charge-transfer insulators

We derive exciton-spin interactions from a microscopic correlated model that captures important aspects of the physics of charge-transfer (CT) insulators to address magnetism associated with exciton creation. We present a minimal model consisting of coupled clusters of transition metal d and ligand p orbitals that captures the essential features of the local atomic and electronic structure. First, we identify the lowest-energy state and optically allowed excited states within a cluster by applying the molecular orbital picture to the ligand p orbitals. Then, we derive the effective interactions between two clusters mediated by intercluster hoppings, which include exciton-spin couplings. The interplay of the correlations and the spatial structure of the CT exciton leads to strong magnetic exchange couplings with spatial anisotropy. Finally, we calculate an optical excitation spectrum in our effective model to obtain insights into magnetic sidebands optically observed in magnetic materials. We demonstrate that the spin-flip excitation due to the strongly enhanced local spin interactions around the exciton gives rise to the magnetic sidebands.

cond-mat.str-el↗

arXiv2023

Revealing the frequency-dependent oscillations in the nonlinear terahertz response induced by the Josephson current

Nonlinear responses of superconductors to intense terahertz radiation has been an active research frontier. Using terahertz pump-terahertz probe spectroscopy, we investigate the c-axis nonlinear optical response of a high-temperature superconducting cuprate. After excitation by a single-cycle terahertz pump pulse, the reflectivity of the probe pulse oscillates as the pump-probe delay is varied. Interestingly, the oscillatory central frequency scales linearly with the probe frequency, a fact widely overlooked in pump-probe experiments. By theoretically solving the nonlinear optical reflection problem on the interface, we show that our observation is well explained by the Josephson-type third-order nonlinear electrodynamics, together with the emission coefficient from inside the material into free space. The latter results in a strong enhancement of the emitted signal whose physical frequency is around the Josephson plasma edge. Our result offers a benchmark for and new insights into strong-field terahertz spectroscopy of related quantum materials.

cond-mat.supr-con↗